A3: Incarceration
Introduction
The American prison system is one example of the racist and discriminatory foundation of this country. Mass incarceration is a huge problem in the U.S that disproportionately affects marginalized groups of people. Disparities in the demographics of our prison population highlights the bias people of color, and specifically Black Americans face in our current justice system. In order to properly address this issue and strive for reform, it is crucial to research and analyze data.
For the purpose of this analysis I will be looking at variables on the Vera Institue incarceration data such as Year, Race, jail population rates, urbanicity, and county. These can allow us to draw conclusions about trends over time, the disparities in prison population on race and identify trends based on geographic location.
Summary Information
Using the Washington state jail rates dataframe, I found that in 1999, the average total jail population rate was 221.0728205, compared to 326.674359 in 2018. We see a huge increase in the total prison rate from the earliest to latest date in this dataset. Next, I decided to determine the overall highest jail population rates for inmates across different race categories. The highest overall rate for Black incarcerated Americans was 31000 per 100,000. The highest overall jail population rate for White incarcerated Americans was 865.49 per 100,000. Finally, I calculated the highest jail rate for AAPI inmates which was 41750.
The Dataset
Who collected the data?
This data was collected by the Vera Institute.
How was the data collected or generated?
This data was generated by aggregating data from the Bureau of Justice Statistics (BJS), Census of Jails (COJ), and the Annual Survey of Jails (ASJ). This data goes back to 1970, but in recent years Vera took a new approach to merge data at the county level to research incarceration at a deeper level.
Why was the data collected?
Mass incarceration is a huge social issue in our country. Past analysis has shown trend at the state level; however, to truly adress this issue we should also look at data at more specific level. Through county data reform can be made at a community level.
How many observations (rows) are in your data?
There are 1131 rows in this data.
How many features (columns) are in the data?
There are 23 columns in this data.
What, if any, ethical questions or questions of power do you need to consider when working with this data? What are possible limitations or problems with this data?
When working with this data it is important to understand that some of the definitions and interpretations of certain variables may have changed over time. Since this data is quite extensive it may be missing important cultural context that’s emerged over time. For instance, there has been recent discourse over the Census surveys and their categories of race. Minorities such as MENA Americans and Latinx Americans have often had to choose white on these surveys despite identifying as POC. A big limitation in this data is also the missing values. In order to complete my analysis I had to find years that had sufficient data and even so there may be inconsistencies which call for further analyses.
Trends Over Time Chart
The first chart I chose to create highlights the trends of average jail population rate over time based on race. Since the data I use takes the rates rather than the direct number of inmates we can clearly see the discrepancies between Black and White jail populations in this chart. Black jail population rates are substantially higher compared to the White jail population rate in Washington.
Joining, by = "year"
Variable Comparison Chart
I created a chart showing the relationship between urbanicity and average jail population rates to determine if there was any correlation between the two. I was surprised to see that small/mid counties had the highest jail population rates. I also made a bar chart depicting the average black jail population rate over time. We can observe that these rates were especially high in 1997 and 1998 and have gotten lower in recent years.
Map
Finally, I created a map to display the black jail population rate by county for 2018. Through this charty we can see the distribution of black jail rates across the country.
##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layout